Mailman 3 - Python-announce-list

PyCA cryptography 46.0.7 released
by Paul Kehrer April 7, 2026

April 7, 2026

PyCA cryptography 46.0.7 has been released to PyPI. cryptography includes both high level recipes and low level interfaces to common cryptographic algorithms such as symmetric ciphers, asymmetric algorithms, message digests, X.509, key derivation functions, and much more. We support Python 3.8+, and PyPy3 3.11. Changelog (https://cryptography.io/en/latest/changelog/#v46-0-7) * **SECURITY ISSUE**: Fixed an issue where non-contiguous buffers could be passed to APIs that accept Python buffers, which could lead to buffer overflow. **CVE-2026-39892** * Updated Windows, macOS, and Linux wheels to be compiled with OpenSSL 3.5.6. -Paul Kehrer (reaperhulk)

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pytest-9.0.3
by Ran Benita April 7, 2026

April 7, 2026

pytest-9.0.3 ======================================= pytest 9.0.3 has just been released to PyPI. This is a bug-fix release, being a drop-in replacement. The full changelog is available at https://docs.pytest.org/en/stable/changelog.html. Thanks to all of the contributors to this release: * Aditya Giri * Alejandro Villate * Bruno Oliveira * Bubble-Interface * Charles-Meldhine Madi Mnemoi * DavidAG * Denis Cherednichenko * Dr Alex Mitre * Freya * Freya Bruhin * Hugo van Kemenade * John Litborn * Liam DeVoe * Lily Wu * Maxime Grenu * Ran Benita * Randy Döring * Ronald Eddy Jr * Samuel Newbold * Tejas Verma * Vladimir * jxramos * 🇺🇦 Sviatoslav Sydorenko (Святослав Сидоренко) Happy testing, The pytest Development Team

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Pygments 2.19.1 released
by Matthäus G. Chajdas March 29, 2026

March 29, 2026

I'm happy to announce the release of Pygments 2.20.0. Pygments is a generic syntax highlighter written in Python. Pygments 2.20.0 is a major release addressing many bugs and also adding a new lexer. See <https://pygments.org/docs/changelog/> for details. Report bugs and feature requests in the issue tracker: <https://github.com/pygments/pygments/issues>. Thanks go to all the contributors of these lexers, and to all those who reported bugs and waited patiently for this release. Download it from <https://pypi.org/project/Pygments/>, or look at the demonstration at <https://pygments.org/demo/>. Enjoy, Matthäus

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NumPy 2.4.4 Released
by Charles R Harris March 29, 2026

March 29, 2026

Hi All, On behalf of the NumPy team, I'm pleased to announce the release of NumPy 2.4.4. NumPy 2.4.4 is a patch release that fixes bugs discovered after the 2.4.3 release. It should finally close issue #30816, the OpenBLAS threading problem on ARM. This release supports Python versions 3.11-3.14. Wheels can be downloaded from PyPI <https://pypi.org/project/numpy/2.4.4>; release notes and the changelog are available on Github <https://github.com/numpy/numpy/releases/tag/v2.4.4>. *Contributors* A total of 8 people contributed to this release. People with a \"+\" by their names contributed a patch for the first time. - Charles Harris - Daniel Haag + - Denis Prokopenko + - Harshith J + - Koki Watanabe - Marten van Kerkwijk - Matti Picus - Nathan Goldbaum *Pull requests merged* A total of 7 pull requests were merged for this release. - #30978: MAINT: Prepare 2.4.x for further development - #31049: BUG: Add test to reproduce problem described in #30816 (#30818) - #31052: BUG: fix FNV-1a 64-bit selection by using NPY_SIZEOF_UINTP (#31035) - #31053: BUG: avoid warning on ufunc with where=True and no output - #31058: DOC: document caveats of ndarray.resize on 3.14 and newer - #31079: TST: fix POWER VSX feature mapping (#30801) - #31084: MAINT: numpy.i: Replace deprecated `sprintf` with `snprintf`... Cheers, Charles Harris

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pymemtrace 0.3.1 is released
by Paul Ross March 23, 2026

March 23, 2026

I am proud to announce version 0.3.1 of pymemtrace, a collection of tools for tracking the memory usage of Python objects and processes. Two new tools have been added: - process_tree.py is capable of logging a process *and* all of its children. This reports other resource usage, such as CPU%, as well as memory. Examples: https://pymemtrace.readthedocs.io/en/latest/examples/process_tree.html - The cPyMemTrace module now has *Reference Tracing <https://docs.python.org/3/c-api/profiling.html#reference-tracing>* (Python 3.13+) that can record every Python object allocation and de-allocation. Examples: https://pymemtrace.readthedocs.io/en/latest/examples/c_py_mem_trace.html#re… A complete description of all the tools, with worked examples, is in the PyPi description: https://pypi.org/project/pymemtrace/#description Other changes: - Add a decorator for process.py. - cPyMemTrace: - Add decorators for Python functions for Profile, Trace and ReferenceTracing. - Add an option to log to a specific file. - Add an API write_message_to_log() to inject text into the log file. - Better structure of the log file format. - Fix stacking pop() issue with trace/profile functions with a linked list of tTraceFileWrapperLinkedList. - Add support for Python 3.14, remove support for Python 3.7 - Supported Python versions are: 3.8, 3.9, 3.10, 3.11, 3.12, 3.13, 3.14 - The extensive documentation, with worked examples, now runs to 120+ pages. - Development Status :: 5 - Production/Stable PyPi: https://pypi.org/project/pymemtrace Documentation: https://pymemtrace.readthedocs.io/en/latest/index.html Project: https://github.com/paulross/pymemtrace Paul Ross

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NumPy 2.4.3 Release
by Charles R Harris March 9, 2026

March 9, 2026

Hi All, On behalf of the NumPy team, I'm pleased to announce the release of NumPy 2.4.3. The NumPy 2.4.3 is a patch release that fixes bugs discovered after the 2.4.2 release. The most user visible fix may be a threading fix for OpenBLAS on ARM, closing issue #30816. This release supports Python versions 3.11-3.14. Wheels can be downloaded from PyPI <https://pypi.org/project/numpy/2.4.3>; release notes and the changelog are available on Github <https://github.com/numpy/numpy/releases/tag/v2.4.3>. *Contributors* A total of 11 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Antareep Sarkar + - Charles Harris - Joren Hammudoglu - Matthieu Darbois - Matti Picus - Nathan Goldbaum - Peter Hawkins - Pieter Eendebak - Sebastian Berg - Warren Weckesser - stratakis + *Pull requests merged* A total of 14 pull requests were merged for this release. - #30759: MAINT: Prepare 2.4.x for further development - #30827: BUG: Fix some leaks found via LeakSanitizer (#30756) - #30841: MAINT: Synchronize 2.4.x submodules with main - #30849: TYP: matlib: missing extended precision imports - #30850: BUG: Fix weak hash function in np.isin(). (#30840) - #30921: BUG: fix infinite recursion in np.ma.flatten_structured_array... - #30922: BUG: Fix buffer overrun in CPU baseline validation (#30877) - #30923: BUG: Fix busdaycalendar's handling of a bool array weekmask... - #30924: BUG: Fix reference leaks and NULL pointer dereferences (#30908) - #30925: MAINT: fix two minor issues noticed when touching the C API setup - #30955: ENH: Test .kind not .char in np.testing.assert_equal (#30879) - #30957: BUG: fix type issues in uses if PyDataType macros - #30958: MAINT: Don't use vulture 2.15, it has false positives - #30973: MAINT: update openblas (#30961) Cheers, Charles Harris

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Vulture 2.15
by Jendrik Seipp March 4, 2026

March 4, 2026

Vulture - Find dead code ======================== Vulture finds unused code in Python programs. This is useful for cleaning up and finding errors in large code bases. If you run Vulture on both your library and test suite you can find untested code. Due to Python's dynamic nature, static code analyzers like Vulture are likely to miss some dead code. Also, code that is only called implicitly may be reported as unused. Nonetheless, Vulture can be a helpful tool for higher code quality. Download ======== https://github.com/jendrikseipp/vulture http://pypi.python.org/pypi/vulture Features ======== * fast: uses static code analysis * tested: tests itself and has complete test coverage * complements pyflakes and has the same output syntax * sorts unused classes and functions by size with `--sort-by-size` News ==== * Handle `while True` loops without `break` statements (kreathon). * Add whitelist for `ssl.SSLContext` (tunnelsociety, #392). * Add more ruff rules (even-even). * Drop support for Python 3.8 (Jendrik Seipp, #398). * Add support for Python 3.14 (even-even). Cheers, Jendrik

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Announcing delb 0.6, a Python library for XML encoded text
by delb project Feb. 22, 2026

Feb. 22, 2026

I'm happy to announce the release of *delb* 0.6 that marks a significant milestone for the project. It was started as an experimental prototype out of frustration with the available Python tools to process XML encoded textual data, namely those according to the guidelines of the *Text Encooding Initiative*, and was thus named by the abbreviation for *Donde esta la biblioteca?* This newest incarnation is a completely native implementation of its data model with a matured and stable API. The functional extent is kept low-level enough to build further XML related tools and domain specific applications with it. The current main selling points at a glance are: - XML DOM types are represented by distinct classes. - A completely type-annotated API with consistent naming and callables’ signatures. - Loads documents from various source types. - Easy, simply filterable traversing of a document in all directions staring from any node. - Shadows comments and processing instructions by default. - Querying with XPath and CSS expressions. - Serializations that may fulfil the promise of XML’s well-readability to an unwitnessed degree and even don’t mess up whitespace. - Optional whitespace handling per TEI recommendation. - Various customization opportunities (document loaders & representations, XML parser, XPath functions). - It’s well tested. PyPI: https://pypi.org/project/delb Documentation: https://delb.readthedocs.io/0.6/ Also recommended to check out are: - An extension to interact with eXist-db instances: https://pypi.org/project/delb-existdb/ - Danny Pudi's & Donald Glover's performance: https://www.youtube.com/watch?v=j2IDOMuHpWY Feel free to forward this email to interested engineers in the field of Digital Humanities and please excuse redundant deliveries. Best regards, Frank

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[ANN] PyData/Sparse 0.18.0 released
by Hameer Abbasi Feb. 18, 2026

Feb. 18, 2026

PyData/Sparse is a library providing N-dimensional sparse arrays for the PyData ecosystem. This release focuses on expanded array API compatibility, developer experience, and QoL fixes. Repo: https://github.com/pydata/sparse Docs: https://sparse.pydata.org/en/0.18.0/ Issue Tracker: https://github.com/pydata/sparse/issues Changelog What's Changed * Implementing `repeat` function by @prady0t in https://github.com/pydata/sparse/pull/875 * Adding `tile` function by @prady0t in https://github.com/pydata/sparse/pull/880 * Setting `boolean indexing` flag to False by @prady0t in https://github.com/pydata/sparse/pull/884 * Adding `unstack` function by @prady0t in https://github.com/pydata/sparse/pull/883 * Fixing `check_zero_fill_value` by @prady0t in https://github.com/pydata/sparse/pull/886 * Running codecov only when tests pass by @prady0t in https://github.com/pydata/sparse/pull/887 * Adding `diff` function by @prady0t in https://github.com/pydata/sparse/pull/888 * Making benchmarking tests deterministic by @prady0t in https://github.com/pydata/sparse/pull/891 * Migration guide by @hameerabbasi in https://github.com/pydata/sparse/pull/898 * Lock mlir to python <3.14 by @prady0t in https://github.com/pydata/sparse/pull/906 * feat: Add sparse.interp function for numba backend by @peanutfun in https://github.com/pydata/sparse/pull/903 * Update Finch notebook by @mtsokol in https://github.com/pydata/sparse/pull/911 * BUG: asarray: fix default format for `SparseArray` input by @lucascolley in https://github.com/pydata/sparse/pull/918 * [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in https://github.com/pydata/sparse/pull/916 * BLD/DEV/CI: better Pixi setup by @lucascolley in https://github.com/pydata/sparse/pull/920 * ENH: transition to SciPy sparse arrays from matrices by @lucascolley in https://github.com/pydata/sparse/pull/919 * DEV/CI: use Pixi for examples, notebooks, and xp-tests by @lucascolley in https://github.com/pydata/sparse/pull/922 New Contributors * @peanutfun made their first contribution in https://github.com/pydata/sparse/pull/903 * @lucascolley made their first contribution in https://github.com/pydata/sparse/pull/918 Full Changelog: https://github.com/pydata/sparse/compare/0.17.0...0.18.0

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TatSu v5.17.0
by Juancarlo Añez Feb. 16, 2026

Feb. 16, 2026

竜 TatSu is a tool that takes grammars in a superset of EBNF as input, and outputs memoizing (Packrat) PEG parsers in Python. The classic variations of EBNF (Tomassetti, EasyExtend, Wirth) and ISO EBNF are also supported as input grammar format. The Overdue Major Refactoring ------------------------------------------ Maintenance and contributions to TatSu have been more difficult than necessary because of the way the code evolved through its lifetime. - Very long modules and classes that try to do too much - Algorithms difficult to understand or with incorrect semantics - Basic features missing, because the above made them hard to implement This release is a major refactoring of the code in TatSu. - Complex modules were partitioned into sub-modules and classes with well-defined purpose - Several algorithms were rewritten to make their semantics clear and evident, and their implementation more efficient - Many unit tests were added to assert the semantics of complex algorithms - Several user-facing features were added as they became easier to implement For the details about the many changes please take a look at the commit log. - pypi: https://pypi.org/project/TatSu/ - docs: https://tatsu.readthedocs.io/ - repo: https://github.com/neogeny/TatSu Every effort has been made to preserve backwards compatibility by keeping most unit tests intact and testing with projects with large grammars and complex processing. If something escaped those tests, there will be a bugfix release with the fixes soon enough. User-Facing Changes - The TatSu documentation has been improved and expanded, and it has a better look&feel with improved navigation. - TatSu doesn’t care about file names, but the default extension used in unit tests, examples, and documentation for grammars is now .tatsu - EBNF, both ISO and the classic variations, is fully supported as grammar input format - Now tatsu.parse(...., asmodel=True) produces a model that matches the ::Type declarations in their grammar (see the models documentation for a thorough review of the features). - walkers.NodeWalker now handles all known types of input. Also: - DepthFirstWalker was reimplemented to ensure DFS semantics - PostOrderDepthFirstWalker walks children before parents - PreOrderWalker was broken and crazy. It was rewritten as a BreadthFirstWalker with the correct semantics - Constant expressions in a grammar are now evaluated deeply with multiple passes of eval() as to produce results that are intuitively correct: def test_constant_math(): grammar = r""" start = a:`7` b:`2` @:```{a} / {b}``` $ ; """ result = parse(grammar, '', trace=True) assert result == 3.5 - Evaluation of Python expressions by the parsing engine now use safe_eval(), a hardened firewall around most security attacks targeting eval() (see the safeeval module for details) - Because None is a valid initial value for attributes and a frequent return value for callables, the required logic for undefined values was moved to the notnone module, which declares Undefined as an alias for notnone.NotNone In [1]: from tatsu.util.undefined import Undefined In [2]: u = Undefined In [3]: u is None Out[3]: False In [4]: u is Undefined Out[4]: True In [5]: Undefined is None Out[5]: False In [6]: d = u or 'OK' In [7]: d Out[7]: 'OK' - objectmodel.Node was rewritten to give it clear semantics and efficiency - New attributes to Node after initialization generate a warning if the name of a method is being shadowed. This change avoids confusing @dataclass, which is used in generated object models. - Node equality is explicitly defined as object identity. No attempts are made at comparing Node structurally. - Node.children() has the expected semantics, and is much more efficient. - Node.parseinfo is now honored by the parsing engine (previously, only results of type AST could have a parseinfo). Generation of parseinfo is disabled by default, and is enabled by passing pareseinfo=True to the API entry points. def test_node_parseinfo(self): grammar = """ @@grammar :: Test start::Test = true | false ; true = "test" @:`True` $; false = "test" @:`False` $; """ text = 'test' node = tatsu.parse(grammar, text, asmodel=True, parseinfo=True, ) assert type(node).__name__ == 'Test' assert node.ast is True assert node.parseinfo is not None assert node.parseinfo.pos == 0 assert node.parseinfo.endpos == len(text) - Synthetic classes created by synth.synthetize() during parsing with ModelBuilderSemantics behave more consistently, and now have a base class of class SynthNode(BaseNode) - Now ast.AST has consistent semantics of a dict that allows access to contents using the attribute interface - asjson() and friends now cover all known cases with improved consistency and efficiency, so there are less demands over clients of the API - Entry points no longer list a large subset of the configuration options defined in ParserConfig, but still accept them through **settings keyword arguments. Now ParserConfig verifies that the settings passed to are valid, eliminating the frustration of passing an incorrect setting name (a typo) and hoping it has the intended effect. - TatSu still has no library dependencies for its core functionality, but several libraries are used during its development and testing. The TatSu development configuration uses uv and hatch. Several requirements-xyz.txt files are generated in favor of those using pip with pyenv, virtualenvwrapper, or virtualenv - All attempts at recovering comments from parsed input were removed. It never worked, so it had no use. Comment recovery may be attempted in the future. - All pre-existing grammars are compatible with this version of TatSu. - Previously generated Python parsers and models, work with this version of TatSu, yet you should consider generating them anew to take advantage of the improved speed, layout, and features. - CAVEAT: Several functions, methods, and argument names were deprecated. They can still be used, but warnings will be issued at runtime. - CAVEAT: If there are invalid strings or regex patterns in your grammars YOU MUST fix them because now the grammar parser validates strings and patterns. - Many of the functions that TatSu defines for its own use are useful in other contexts. Some examples are: from tatsu.safeeval import is_eval_safe from tatsu.safeeval import hasshable from tatsu.safeeval import make_hashable from tatsu.util import safe_name from tatsu.util.misc import find_from_rematch from tatsu.util.misc import topsort from tatsu.util.undefined import Undefined # ... ----------------------------------------------------------------------------------------------- -- Juancarlo Añez mailto:apalala@gmail.com

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